• Journal of Information Processing Systems
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• v.6 no.2
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• pp.235-252
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• 2010

Regression testing is a very costly process performed primarily as a software maintenance activity. It is the process of retesting the modified parts of the software and ensuring that no new errors have been introduced into previously tested source code due to these modifications. A regression test selection technique selects an appropriate number of test cases from a test suite that might expose a fault in the modified program. In this paper, we propose both a regression test selection and prioritization technique. We implemented our regression test selection technique and demonstrated in two case studies that our technique is effective regarding selecting and prioritizing test cases. The results show that our technique may significantly reduce the number of test cases and thus the cost and resources for performing regression testing on modified software.

• Journal of Information Technology Services
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• v.2 no.1
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• pp.123-133
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• 2003

Because of rapid evolution of software technique, numerous software professionals have been concerned with component based development methodologies. However, it is hard to find out a systematic technique for the selection of COTS (Commercial Off The Shelf) component in consumer position. Up to date, the major of component quality evaluation is object-oriented metric based evaluation methodology. But this paper present four step process and evaluation criteria based on MCDM (Multiple Criteria Decision Making) technique for optimal COTS component selection in consumer position. Weconsidered funtionality, efficiency, usability based on ISO/IEC 9126 for quality measurement and executed practical analysis about commercial EJB component in internet. This paper show that the proposed selection technique is applicable to optimal COTS component selection.

• Journal of the HCI Society of Korea
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• v.9 no.2
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• pp.33-40
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• 2014

Selecting appropriate features that products or services should provide for users has been a critical decision making problem for designers. However, the existing feature selection methods have prominent limitations when figuring out how they perceive the features. For example, selecting features based on the users' preference without analyzing users' mental models might lead to the 'feature creep' phenomenon. In this study, we suggest the 'False belief technique' that is able to detect users' mental model for the products/services that are formed after being provided with new features. This technique will be utilized as a way forward to help the designer to determine what features should be included in the new product development.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.747-749
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• 2017

In this paper, we propose a novel precoder selection technique for maximum-likelihood (ML) detected spatially multiplexed multiple-input multiple-output (MIMO) systems. Previous precoder selection techniques were designed without considering UEP, however the proposed technique is designed considering multi-antenna unequal error protection (UEP). Simulations demonstrate the improved multi-antenna UEP performance by the proposed technique.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.221-222
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• 2008

We propose a LLR (log-likelihood ratio) selection combining technique that reduces much of complexity. This technique chooses the most reliable branch based on the magnitude of the LLR of each branch. We show that the proposed selection combining achieves significant power gains over conventional selection combining and nearly matches the performance provided by MRC.

• Journal of the Korean Institute of Telematics and Electronics
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• v.4 no.4
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• pp.19-21
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• 1967

A technique is illustrated for the selection of basis rows from a cyclic prime implicant table. This technique is more systematic and effective than a trial and process, and the results of this technique agree well with the ones solved by Gimpel's Luccio's reduction technique.

• Proceedings of the KOSOMBE Conference
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• v.1989 no.05
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• pp.51-54
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• 1989

In last several years, a number of volume localization techniques, such as ISIS, VSE, SPARS and STEAM etc., have been developed for the MR spectroscopy. These localizing techniques, however, require application of several RF pulses for the 3-D volume selection and suffer from T1 and T2 decays due to relatively long RF excitation time. In this paper, we propose a single-shot RF pulse localization technique to achieve the localized 3-D volume selection. This technique combines the cylindrical volume selection technique with a radial gradient coil with single-shot RF pulse and the oscillating selection gradient technique, so thai it minimizes the volume selection time. We report some experimental results obtained with the proposed method which appears promising for 3-D volume imaging and localized spectroscopy.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.55-66
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• 2024

Gender classification techniques have received a lot of attention from researchers because they can be used in various fields such as forensics, surveillance systems, and demographic studies. As previous studies have shown that there are distinctive features between male and female gait, various techniques have been proposed to classify gender from three dimensional(3-D) gait data. However, some of the gait features extracted from 3-D gait data using existing techniques are similar or redundant to each other or do not help in gender classification. In this study, we propose a method to select features that are useful for gender classification using a correlation-based feature selection technique. To demonstrate the effectiveness of the proposed feature selection technique, we compare the performance of gender classification models before and after applying the proposed feature selection technique using a 3-D gait dataset available on the Internet. Eight machine learning algorithms applicable to binary classification problems were utilized in the experiments. The experimental results show that the proposed feature selection technique can reduce the number of features by 22, from 82 to 60, while maintaining the gender classification performance.

• ETRI Journal
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• v.30 no.1
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• pp.89-100
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• 2008

We consider the feature recombination technique in a multiband approach to speaker identification and verification. To overcome the ineffectiveness of conventional feature recombination in broadband noisy environments, we propose a new subband feature recombination which uses subband likelihoods and a subband reliable-feature selection technique with an adaptive noise model. In the decision step of speaker recognition, a few very low unreliable feature likelihood scores can cause a speaker recognition system to make an incorrect decision. To overcome this problem, reliable-feature selection adjusts the likelihood scores of an unreliable feature by comparison with those of an adaptive noise model, which is estimated by the maximum a posteriori adaptation technique using noise features directly obtained from noisy test speech. To evaluate the effectiveness of the proposed methods in noisy environments, we use the TIMIT database and the NTIMIT database, which is the corresponding telephone version of TIMIT database. The proposed subband feature recombination with subband reliable-feature selection achieves better performance than the conventional feature recombination system with reliable-feature selection.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.45-55
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• 1989

This paper deals with development of a computer-aided process selection and sequencing technique and its software for metal cutting processes of rotational parts. The process selection procedure consists of selection for proper machining operations and machine tools suitable for the selected operations. Machining operations are selected based on machining surface features and machine tools are selected by employing a conversion table which converts machining operations into machine tools. The process sequence is determined by the proper manipulation of the precedence relation matrix. A computer program for the proposed technique is developed by using Turbo-Pascal on IBM PC/AT compatible system. The proposed technique works well to real problems.